Transport Mode Choice Research Articles

Discrete Choice Models and Artificial Intelligence Techniques for Predicting the Determinants of Transport Mode Choice—A Systematic Review

Discrete Choice Models and Artificial Intelligence Techniques for Predicting the Determinants of Transport Mode Choice—A Systematic Review

The Influence Of Green Transportation And Gen Z Consumer Behavior On The Selection Of Biskita Trans Pakuan Transportation Mode

Concern over sustainable transportation is growing as the demand for environmentally friendly alternatives increases. This study examines the impact of green transportation and Gen Z consumer behaviour as independent variables on the choice of transportation mode. The findings correspond with other studies, emphasizing the importance of green transportation and consumer behaviour in affecting the mode of transportation chosen. The purpose is to examine the direct correlation between green transport and the behaviour of Gen Z consumers, considering them as independent variables that impact the choice of transportation mode as the dependent variable. The sample comprised participants who had utilised Biskita transport on at least one occasion. They were residents of Bogor city, born between 1996 and 2010. The study aimed to investigate the influence of green transportation and Gen Z consumer behaviour on mode choice. Path analysis was conducted in order to understand the direct effects of relationship between variables. Data analysis was carried out using Smart PLS software. This study is constrained by the limited amount of available data and a small sample size of participants. The results is green transportation and gen z consumer behaviour have a significant direct influence on transport mode choice. Green transportation is critical in providing information that increases consumer awareness of environmental issues and enables consumer behaviour to better respond to external pressures and encourages consideration of environmental issues when making decisions on the mode of transport used and implementing actions that increase the likelihood of achieving optimal mode choice.
 
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KAJIAN RESPON PENAMBAHAN GERBONG WANITA PADA LRT PALEMBANG

LRT (Light Rail Transit) is a fast and efficient transportation mode option. Women are one of the LRT transportation users with various obstacles, such as the level of security, which often does not receive special attention. The demands on women's time limit their ability to increase income productivity, and isolate them. So in several public transportations, including the LRT, women-only carriages have been added so that female passengers feel safe. In the process of avoiding violence in public transportation, there is a plan to have special women's carriages on the Palembang LRT. This research is to see the response of Palembang LRT users to whether it is necessary to add special women's carriages to avoid violence that occurs on the Palembang LRT and also to see the performance conditions of the Palembang LRT as a choice of transportation mode for the community.

Revealing the Impacts of the Pandemic on Travel Behavior by Examining Pre- and Post-COVID-19 Surveys

Recently, the topic of travel behavior and social media usage has been widely discussed. The current study specifically focuses on how specific factors, such as the sociodemographic variables, the number of friends, the social media usage, and the ICT usage, influence their travel patterns based on survey results conducted in pre- and post-COVID-19 times. The effect of the COVID-19 pandemic is taken into consideration to better understand the impact of restrictions on travel attitudes. Statistical analysis is carried out to investigate the survey data. The results show that the pandemic has made a huge impact on general travel behavior, especially in terms of transport mode choice shifting towards individual modes, such as car and walking. The location choice of the participants has a significant connection to the available transport mode and the price range of the place, together with the retrieved information from the ICT devices. Based on the results, it can be seen that the pandemic has deepened the number of close friendships, but younger people do not tend to choose trendy places anymore. In addition, the results show that there is no direct connection between the number of friends and the number of meetings, and the daily online meetings have not replaced all personal meetings.

Competitiveness of modes of transport in Kazakhstan: influencing factors and rating

This article discusses the competitiveness of various modes of transport in Kazakhstan and provides an assessment of the main factors influencing the choice of transportation modes within the realm of economics. The comprehensive rating system aimed at evaluating the competitiveness of different transportation modes in Kazakhstan. Drawing upon various perspectives and analytical methodologies, this system proves to be a valuable tool for politicians and stakeholders seeking to optimize Kazakhstan transportation system. The primary objective of this study is to examine which of the selected factors has the most significant impact on Kazakhstan's decisions regarding the choice of transportation vehicles. The thorough analysis of key literature sources was carried out and a methodology based on our findings was selected. The methodological approach involves the creation of multi-factor regression models utilizing the EViews10 data analysis software package. The research dataset encompasses data from the Bureau of National Statistics of the Republic of Kazakhstan's Agency for Strategic Planning and Reforms for the years 2013 to 2022. Calculations derived from our research revealed that the selected factors have varying effects on different types of transportation. As a result of this study, it becomes possible to formulate recommendations for state policies in the realm of transportation infrastructure and its implications for economic and social development, with a specific focus on enhancing vehicle capacity. The study's findings are of relevance to transportation companies and governmental entities responsible for managing the transportation system.

PANDEMIC IMPACT ON TRAFFIC TRENDS AND PATTERNS IN THE CITY OF BELGRADE

The appearance of the COVID-19 virus has caused great changes in all spheres of life. Probably the most visible change is the cities’ lockdown, with the suspension of traffic and transport systems. The capital of the Serbia – Belgrade also went through a complete lockdown, which lasted for almost 2 months (53 days). In that period, nearly all activities were reduced, producing significant losses for the whole economic development, healthcare, food supply chain, transport sector and most importantly public transport system. The behaviour of users in such situations can greatly influence the change in the share of certain modes of transport in the overall modal share. The aim of this article is to examine the influence of the COVID-19 pandemic on the transport mode choice for different trip purposes, as well as the examination of different impact factors, such as gender, age, education level, employment status, income, transport mode used before the pandemic, and average distance travelled, on the change of mode of transport. Data of 1143 users were analysed through a survey, for the area of the city of Belgrade, using the McNemar–Bowker test and binary logistic regression. The results showed that pandemic had a significant impact on the transport mode change for all trip purposes. The key factors influencing the change in the mode of transport are factors related to gender, level of education, income, the type of transport used before the pandemic and the average distance travelled. It is also interesting to note that the results showed a significant number of transfers to individual modes of transport, as well as micromobility vehicles and walking. Therefore, this article provides the necessary help in understanding the transport system user’s behaviour, which can facilitate the choice of adequate measures, modes and activities for decision-makers in these specific situations.

Does emphasis change in transportation mode choice affect workers’ actual mode choice? Implications from Japan in the COVID-19 era

Although modal shift from private motorized vehicles to public and active transport is regarded as crucially important for a sustainable society, such a shift has not been successful in Japan. One reason may be that measures have not satisfied the latent factors underlying people's transportation mode choices. Moreover, these factors may have changed during the COVID-19 pandemic. This study is aimed at ascertaining what workers have emphasized in transportation mode choice, and how those emphases have affected their actual mode choice. We also examined how changes in individuals' emphases during the pandemic have affected their actual mode choices. We used a four-time panel survey with 1377 respondents from Japan that asked participants about important items related to their transportation mode choice and activity patterns at four time points before and during the COVID-19 pandemic. After conducting a factor analysis to ascertain the latent factors behind mode choice, we applied a logistic regression model showing whether or not the respondents used each transportation mode at each time point. A conditional logistic regression model with individual fixed effect was applied to the relationship between an individual's change in emphasis and actual mode choice. Factor analysis results indicated four latent factors: usability and reliability, personal time–space, attitude toward the environment and health, and ease of use and convenience. A higher emphasis on personal time–space encouraged car use and discouraged public transport use at any time points. This trend became stronger during the pandemic. Changes in the emphasis level of this factor for an individual also affected the actual mode choice. A higher emphasis on usability and reliability also discouraged public transport use. Ease of use and convenience encouraged public transport use, and attitude toward the environment and health neither encouraged nor discouraged actual mode choice at any time point. Emphases related to transportation mode choice changed over time. However, changes in individuals' emphasis altered the actual mode choice at some time points but not at others. These results should be considered in transportation planning in order to prompt desired modal shifts by transportation users.

Transportation Mode Choice Behavior with Multinomial Logit Model: Work and School Trips

Transportation Mode Choice Behavior with Multinomial Logit Model: Work and School Trips

Alternate closed-form weibit-based model for assessing travel choice with an oddball alternative

Herein, a weibit-based model is proposed as an alternative to Recker's logit choice model with an “oddball” alternative, which explicitly focuses on a single alternative that has unique attributes to other conventional alternatives in the choice set [Recker, W.W. (1995). Discrete choice with an oddball alternative. Transportation Research, 29B, 201–212]. While retaining the closed-form probability expression, the proposed model handles the oddball alternative using a multiplicative random disutility function assuming Weibull distributed random components. The proposed model thus allows disutility-dependent perception variances of both the conventional and oddball alternatives and a flexible variance ratio between them, which are effective to reflect the way how individuals perceive varying magnitudes of travel disutility from different attributes. This gives the proposed model more flexibility to consider various heterogeneity issues, including the heterogeneous perceptions of conventional alternatives, heterogeneous perceptions of unique and common attributes of the oddball alternative, and heterogeneous features of conventional and oddball alternatives. The empirical application of the proposed model is explored to highlight its practical performance. The results demonstrate the superiority of the proposed model in the choice contexts where both oddball effect and heterogeneity issues need to be considered. The proposed model could further provide new behavioral insights into various decision-making scenarios of transportation networks, such as transportation mode choices in the current era of emerging technologies and destination choices in urban agglomerations.

Effect of the COVID-19 pandemic on crowding aversion in public transport and transport mode choice: The case of Santiago, Chile

Mode choice modeling has shown a significant crowding effect over travel time perception. But the recent COVID-19 pandemic and the related sanitary measures have changed perceptions of overcrowding on the mode choice. This study aims to quantify these changes through a hybrid discrete choice model using data collected through a revealed preferences survey applied in two time periods in Santiago, Chile. Although the overcrowding aversion was included in the choice model as a latent variable, that had a significant effect on the mode choice of people only for the set of responses belonging to the first time period, which implies a reduction of the initial pandemic impact. Results also show that women and people younger than 35 years old have higher levels of crowding aversion. By analyzing the disutility generated by each alternative mode, it is determined that the bicycle is preferred over the car for trips of distances less than 4 km. In the same way, for trips of less than 3 km, the walk has a preference over public transport. Regarding the marginal rates of substitution between travel and walking time in public transport, for trips of 30 min with an overcrowding level of 6 pax/m2, women over 35 years are willing to trade 2 min of travel for 1 min of walking. When comparing the rates obtained in a pre-pandemic study, it is obtained that for trips of less than 9 min, people in the pandemic have more preferences for walking over spending time inside public transport.

РОЛЬ ГЕНДЕРНОГО ФАКТОРА ПРИ ВЫБОРЕ СРЕДСТВА ПЕРЕМЕЩЕНИЯ ПО ГОРОДУ

Modern studies of approaches to urban development in general and to urban transport in particular pay great attention to the interests and needs of various population groups. In particular, the factor of gender identity becomes important in the formation of urban transport policy, namely, understanding the need to take into account the different requirements of men and women in the formation and development of urban infrastructure. In this paper, based on the results of empirical data collection, we show that the transportation behavior and factors of transportation mode choice are different for men and women. This allows us to conclude that developing urban transport infrastructure, city authorities have the opportunity not just to meet the needs of representatives of different gender, but also effectively influence the peculiarities of transportation behavior of citizens.

PERSEPSI MASYARAKAT KOTA BOGOR TERHADAP SISTEM PEMBELIAN LAYANAN

The very high number of private vehicles in the city of Bogor will result in traffic congestion and air pollution. This is due to population growth in urban areas every year. In an effort to solve the problem of traffic jams in the city of Bogor, the government is conducting a trial purchase of services. The aim is expected to increase people's use of public transportation, reduce private vehicles, and improve the community's economy. With the purchase of this service, the author aims to find out how the public perceives the purchase of services in the city of Bogor and explains the influence of age, gender, education, occupation, domicile, monthly expenses, and the frequency and choice of public transportation modes on public perceptions regarding BTS services in Bogor city. The author uses a survey method in the form of an online questionnaire as a means of collecting research data. The one-sample t-Test is used as a test method to test the research instrument and is followed by an independent sample t-test method to test the relationship between two populations that have no relationship with one another. Based on the results of the analysis, it can be seen that the majority of people agree with the purchase of this service, which is implemented in the city of Bogor.

Working from home, active travel, health and wellbeing: Legacies of a pandemic

While many studies have explored the impact of COVID-19 and/or working from home (WFH) on the transport network and modal choice, relatively few have looked at the implications of WFH through the lens of physical activity (PA) and the role of active travel moving forward. Drawing from a survey of 1,165 Sydney (Australia) workers conducted in late 2020, after restrictions from the first COVID-19 wave were significantly eased across Australia, we explore the impact of the pandemic on perceived changes in WFH, active travel, physical health, and wellbeing. We identify three distinct segments of the population with differing active travel, PA and quality of life (QoL) outcomes: (1) ‘Active but Anxious’ (22%) – younger, higher income, largest increase in WFH, sitting relatively more, largest relative decrease in active commuting, increased relative PA and largest proportion who are physically active; (2) ‘Less Change, Less Worry’ (38%) – older and male, least change in WFH, least relative change in active commuting, sitting relatively less, largely sufficient PA, highest QoL; (3) ‘Stressed and Sedentary’ (40%) – average age, lower income, largest loss of paid work, highest levels of sitting, lowest PA and QoL. Given WFH remains a prevalent component of the travel activity matrix, we consider the implications of these heterogeneous outcomes for individuals, employers and policy-makers charged with shaping active travel policy and planning in a post-pandemic world.

Pengaruh Kenaikan Harga Bahan Bakar Minyak terhadap Pemilihan Moda Transportasi (Studi Kasus: Perkotaan Yogyakarta)

The increase in world oil prices has led to changes in the price of fuel oil (BBM) in Indonesia. The fuel price change policy impacts various sectors, including the transportation sector. Transportation is one of the basic human needs for moving from one place to another. Various factors are taken into consideration by the community in choosing the mode of transportation to be used. This study aims to analyze the impact of changes in fuel prices on preferences for transportation modes in urban Yogyakarta and to see how people's behaviour changes in mobility. The analytical method used in this research is descriptive and crosstab analysis. Descriptive analysis was used to identify the respondents' characteristics, the journey's characteristics, and the effect of rising fuel prices. Crosstab analysis is used to see the relationship between the characteristics of respondents and the choice of transportation mode before and after the fuel price increase. The data collection method was carried out by distributing questionnaires to the people of Yogyakarta. The choice of transportation mode when fuel oil increases does not change much, whereas in the scenario of changing fuel prices, there is a significant increase. This can be seen from the decrease in car users when there is an increase in the price of fuel oil, while the probability of motorcycle users when the fuel price rises until the fuel price is Rp 12,000 continues to increase, while when the fuel price is Rp 14,000 switch to using public transportation modes, namely the Trans Jogja bus. When the price of fuel oil increases, the frequency of primary trips does not change, while the frequency of secondary trips changes. Transportation costs incurred have increased, and the fuel used has changed; from the first, Pertamax switched to pertalite

Do environmentally sustainable travel behaviours contribute to transportation-related social exclusion?

Travel behaviours of today's young adults may be considered environmentally sustainable. However, the risk of transportation-related social exclusion and consequently socially unsustainable travel behaviour among young adults, which may relate to their sustainable travel choices and lower car-reliance, remains less explored. Focusing on 4178 Canadian post-secondary students within the Greater Toronto and Hamilton Area, we examined four measures of activity participation for each student as indicators of social exclusion which include the number of daily activities, area covered per activity, distance travelled per activity, and time spent travelling per activity. We explored the association between students' activity participation patterns and their transportation mode choice patterns. A latent class analysis of short- and long-term travel choices revealed five transportation mode choice patterns, namely- Automobile Dependents, Transit Dependents, Cyclists, Pedestrians, and Multimodals. Results from Poisson and multiple linear regression models suggest that transportation mode choice patterns are significantly associated with how students participate in activities. Transit Dependents are more likely to face social exclusion due to limited activity participation. Students who reside in dense areas with better street connectivity demonstrate socially sustainable travel patterns. Future transportation planning and policy should be focused on addressing the travel needs of young adults with limited transportation opportunities and inefficient public transit.

Exploring User Experience in Sustainable Transport with Explainable AI Methods Applied to E-Bikes

Sustainable modes of transport are being promoted to achieve global climate goals. The perceived user experience is decisive for the choice of transport mode. To increase the share of sustainable transport in total traffic, the user experience is placed into the spotlight, raising the need for appropriate exploration methods. Machine learning (ML) techniques have become increasingly popular in the transport domain, but the black-box nature of ML models poses significant challenges in interpreting the relationship between model input and output. Explainable AI methods (XAI) can fill this gap by providing post hoc interpretation methods for black-box models. The aim of the present work was therefore to assess the potential of XAI to explore user experience in transport. The introduced method was based on a popular XAI method named SHAP (SHapley Additive exPlanations). Applied to the use case of e-bikes, we aimed to explore factors influencing the riding experience on e-bikes. We applied Gaussian process regression to data collected in a cycling study from 55 e-bike riders including rider behaviour, motor power and riding dynamics. Applying SHAP, we compared the riding experience of four rider types identified by hierarchical cluster analysis. The results provide insights into the riding experience on e-bikes: motor power, rider behaviour and riding dynamics were found to be meaningful predictors differing in their impact between rider types. Our results can be regarded as a proof of concept and demonstrate the potential of XAI to enhance the understanding of user experience in transport.

Daily Travel Mode Choice Considering Carbon Credit Incentive (CCI)—An Application of the Integrated Choice and Latent Variable (ICLV) Model

There have been many implementations of carbon credit incentives (CCIs) for promoting green travel, but research on quantifying the effectiveness remains limited. To fill this gap, this study focuses on residents’ daily transportation mode choices under the incentive of carbon credits by employing an integrated choice and latent variable (ICLV) model to adequately address the role of attitudinal variables related to carbon credits, such as perceived usefulness, perceived ease of use, and behavioral intentions. Data from a questionnaire survey show that the ICLV model provides a richer and more nuanced understanding of the green mode choice than a traditional multinomial logit (MNL) model, where the AIC value of the ICLV model (3901.17) is smaller than that of the MNL model (3910.09). Carbon credits exhibit diverse impacts across various modes of eco-friendly transportation and specific demographic groups. Commuting trips reveal noteworthy positive associations between carbon credits and the use of bicycles as well as metro/bus services. Moreover, carbon credits exert a more pronounced influence on individuals with higher education levels, older age groups, and owners of new energy vehicles, whereas their impact on high-income individuals is relatively constrained. Furthermore, perceptions of carbon credits are pivotal, with perceived utility emerging as the most influential factor. The results provide a scientific basis for formulating more effective policies regarding carbon credit and incentive measures in the future.

Probabilistic Forecasting of Bus Travel Time with a Bayesian Gaussian Mixture Model

Accurate forecasting of bus travel time and its uncertainty is critical to service quality and operation of transit systems: it can help passengers make informed decisions on departure time, route choice, and even transport mode choice, and it also support transit operators on tasks such as crew/vehicle scheduling and timetabling. However, most existing approaches in bus travel time forecasting are based on deterministic models that provide only point estimation. To this end, we develop in this paper a Bayesian probabilistic model for forecasting bus travel time and estimated time of arrival (ETA). To characterize the strong dependencies/interactions between consecutive buses, we concatenate the link travel time vectors and the headway vector from a pair of two adjacent buses as a new augmented variable and model it with a mixture of constrained multivariate Gaussian distributions. This approach can naturally capture the interactions between adjacent buses (e.g., correlated speed and smooth variation of headway), handle missing values in data, and depict the multimodality in bus travel time distributions. Next, we assume different periods in a day share the same set of Gaussian components, and we use time-varying mixing coefficients to characterize the systematic temporal variations in bus operation. For model inference, we develop an efficient Markov chain Monte Carlo (MCMC) algorithm to obtain the posterior distributions of model parameters and make probabilistic forecasting. We test the proposed model using the data from two bus lines in Guangzhou, China. Results show that our approach significantly outperforms baseline models that overlook bus-to-bus interactions, in terms of both predictive means and distributions. Besides forecasting, the parameters of the proposed model contain rich information for understanding/improving the bus service, for example, analyzing link travel time and headway correlation using covariance matrices and understanding time-varying patterns of bus fleet operation from the mixing coefficients. Funding: This research is supported in part by the Fonds de Recherche du Quebec-Societe et Culture (FRQSC) under the NSFC-FRQSC Research Program on Smart Cities and Big Data, the Canadian Statistical Sciences Institute (CANSSI) Collaborative Research Teams grants, and the Natural Sciences and Engineering Research Council (NSERC) of Canada. X. Chen acknowledges funding support from the China Scholarship Council (CSC). Supplemental Material: The e-companion is available at https://doi.org/10.1287/trsc.2022.0214 .

Association of risk perception and transport mode choice during the temporary closure of a major inner-city road bridge: results of a cross-sectional study

BackgroundSince air pollution and physical inactivity pose major public health risks, switching from cars to alternatives like public transport, cycling, and walking is important. Therefore, it is beneficial to identify key events for changes of mode choice.MethodsWe examined the association between risk perception and mode choice during the temporary closure of a road bridge between two major German cities in early 2020 using binary and multinomial regression models.Results679 people participated in the survey. We found that 22% of car users switched to alternatives. The higher the perceived health risk from traffic-related air pollution, the more likely car users switched to alternatives (odds ratio [OR] = 1.76, 95% CI [1.14, 2.71]).DiscussionAttitude, subjective norm and perceived behavioral control were associated with maintaining but not with switching transport modes. In conclusion, the closure of a main road bridge may present a key event. To explain mode choice, risk perception is a potential extension to the theory of planned behavior.

A STUDY ON INTERSTATE FREIGHT MODE CHOICE BETWEEN TRUCKS AND TRAINS USED TO TRANSPORT OIL PRODUCTS: A CASE STUDY OF IRAQ

Freight mode choice is an important stage in shipping demand modeling. Transporting oil products using trucks between cities has several issues, including increased risk of accidents, higher transportation costs, environmental impact, and traffic congestion. Due to the absence of local studies, in addition to the few global studies that deal with freight mode selection used to transport oil derivatives between cities, the aim of the study is to develop transport mode choice models for trucks and trains transporting oil products between the interstate capital of Baghdad and the government of Basra for export. The revealed preference survey was used for 277 goods transport data collected with the help of personal interviews, questionnaires, and government institutions. The collected data were processed using two statistical approaches: binary logistic regression and Firth logistic regression. The study’s findings assist decision-makers in selecting sustainable modes of transport.